---
title: "Deer-vehicle collisions in Scotland, 2000 to 2017"
output:
flexdashboard::flex_dashboard:
theme: cerulean
source_code: embed
---
```{r setup, include=FALSE, message=FALSE}
library(flexdashboard)
library(dplyr)
library(stringr)
library(janitor)
library(sf)
library(lubridate)
library(crosstalk)
library(leaflet)
library(DT)
# read and prep data
dvc_read <- st_read(
"data/DVC_SCOTLAND_ESRI/DVC_SCOTLAND.shp",
stringsAsFactors = FALSE # read factor columns as character
) %>%
st_transform(crs = 4326) %>% # transform coords to latlong
clean_names() %>% mutate_if(is.character, tolower) %>%
mutate(
inc_date = ymd(inc_date), # convert to datetime
# clean up names
deer_speci = if_else(deer_speci == "desppnk", "unknown", deer_speci),
localautho = if_else(localautho == "perth & kinross", "perth_and_kinross", localautho),
road_no = if_else(road_no %in% c("unalloc", "notallocated", "notalloc", "u"), "unknown", road_no),
road_no = if_else(str_detect(road_no, "x") == TRUE, "unknown", road_no)
)
# extract latlong cols from sf geometry and bind back to df
dvc_xy <- as.data.frame(st_coordinates(dvc_read))
dvc <- bind_cols(dvc_read, dvc_xy) %>% rename(latitude = X, longitude = Y)
# create sample for testing
dvc_sample <- sample_n(dvc, 100)
# create shared data object for crosstalk
# dvc_sd <- SharedData$new(dvc)
dvc_sd <- SharedData$new(dvc_sample)
```
Explore {data-icon="ion-stats-bars"}
=====================================
Column {data-width=400}
-----------------------------------------------------------------------
### Filters
Where
```{r}
bscols(
filter_select(
id = "la",
label = "Local Authority",
sharedData = dvc_sd,
group = ~localautho
),
filter_select(
id = "road",
label = "Road",
sharedData = dvc_sd,
group = ~road_no
)
)
```
When
```{r}
bscols(
filter_select(
id = "year",
label = "Year",
sharedData = dvc_sd,
group = ~year
),
filter_select(
id = "month",
label = "Month",
sharedData = dvc_sd,
group = ~inc_month
)
)
```
What
```{r}
filter_select(
id = "species",
label = "Deer species",
sharedData = dvc_sd,
group = ~deer_speci
)
```
### Interactive table
```{r}
dvc_sd %>%
datatable(
filter = "top", # allows filtering on each column
extensions = c(
"Buttons", # add download buttons, etc
"Scroller" # for scrolling down the rows rather than pagination
),
rownames = FALSE, # remove rownames
style = "bootstrap",
class = "compact",
width = "100%",
options = list(
dom = "Blrtip", # specify content (search box, etc)
deferRender = TRUE,
scrollY = 300,
scroller = TRUE,
columnDefs = list(
list(
visible = FALSE,
targets = c(0, 1, 3:5, 9:15)
)
),
buttons = list(
I("colvis"), # turn columns on and off
"csv", # download as .csv
"excel" # download as .xlsx
)
)
)
```
Column {data-width=700}
-----------------------------------------------------------------------
### Interactive map
```{r}
dvc_sd %>%
leaflet() %>%
addProviderTiles(providers$OpenStreetMap) %>%
addAwesomeMarkers(
icon = awesomeIcons(
iconColor = "#FFFFFF",
markerColor = "darkblue",
text = case_when(
dvc_sample$year == "2000" ~ "00",
dvc_sample$year == "2001" ~ "01",
dvc_sample$year == "2002" ~ "02",
dvc_sample$year == "2003" ~ "03",
dvc_sample$year == "2004" ~ "04",
dvc_sample$year == "2005" ~ "05",
dvc_sample$year == "2006" ~ "06",
dvc_sample$year == "2007" ~ "07",
dvc_sample$year == "2008" ~ "08",
dvc_sample$year == "2009" ~ "09",
dvc_sample$year == "2010" ~ "10",
dvc_sample$year == "2011" ~ "11",
dvc_sample$year == "2012" ~ "12",
dvc_sample$year == "2013" ~ "13",
dvc_sample$year == "2014" ~ "14",
dvc_sample$year == "2015" ~ "15",
dvc_sample$year == "2016" ~ "16",
dvc_sample$year == "2017" ~ "17",
TRUE ~ "NA"
)
),
popup = ~paste0(
"
Date: ", dvc_sample$inc_date,
"
LA: ", dvc_sample$localautho,
"
Road: ", dvc_sample$road_no
)
)
```
Information {data-orientation=rows data-icon="fa-info-circle"}
=====================================
###
### How to use
#### Filters
You can:
* select one or more local authorities from the dropdown menu (remove them with your backspace key)
* select one or more Ofsted grades using the checkboxes
* select the phase of education with the checkboxes
* drag the slider to select a pupil count
* drag the slider to filter by the percenatge of pupils receiving free school meals
#### Interactive map
You can:
* click to grab and drag the map around
* zoom with the '+' and '--' buttons (top-left) or with your mouse's scroll wheel
* click a marker to reveal a popup with information about that school
* click the button showing a broken square (top-left under the zoom options) to select points on the map using a window that's draggable (click and hold the grid icon in the upper left) and resizeable (click and drag the white boxes in each corner)
#### Interactive table
You can:
* filter each column by typing in the boxes under each column header
* sort the columns (ascending and descending) by clicking on the column header
* change which columns are visible by clicking the Column visibility button
* click 'CSV' or 'Excel' to download the filtered data to a .csv file or a .xlsx
* see how many entries remain after filtering in the bottom-left, where it says 'Showing X to Y of Z entries'
### Notes
#### Under construction
This tool is under construction. Functionality is missing. The data are just a sample of the original dataset. This will be the case while the tool is in development.
#### Tools
[R v3.5.1](https://www.r-project.org/) and [RStudio v1.1.463](https://www.rstudio.com/) were used.
Packages used were
* [Flexdashboard](https://rmarkdown.rstudio.com/flexdashboard/) to create a frame for the content
* [Leaflet](https://rstudio.github.io/leaflet/) for the interactive map
* [DT](https://rstudio.github.io/DT/) for the interactive table
* [Crosstalk](https://rstudio.github.io/crosstalk/) for widget interactivity
* TODO: add more
The code for this tool is available from [github.com/matt-dray/scot-deer-collision](https://github.com/matt-dray/scot-deer-collision).
